Various techniques (e.g., SAE® J361) that are used to evaluate the properties of complex coating (e.g., paint) mixtures typically include a variety of in-plane viewing conditions that are often combined with microscopic evaluation of a sample. However, such techniques generally do not adequately address new effect pigmentations in complex paint mixtures. Further, they are largely focused on textiles and use obscurely identified out-of-plane viewing angles that require at least two light sources for viewing effect pigmentations properly. Other techniques involve using a spectrophotometer (i.e., in-plane multi-angle devices for effect samples and spherical devices for straight shade samples) that are generally effective for analyzing pigmentations. However, such techniques are generally not able to adequately characterize new pigments due to the unique properties of, for example, Colorstream® pigments that include pearls, colored aluminums, etc. because it is very difficult to view the coarseness of colored aluminums. Thus, a microscope is required to adequately determine special effect pigments, thus adding time and complexity while not satisfactorily addressing application issues which modify the characteristics of the sample and the effect of the special pigments.
Laboratory gonio spectrophotometers are not able to be effectively used in either the field or the laboratory due to constraints such as size, cost, performance, and measurement time. Portable gonio spectrophotometer devices include CCD cameras such as the Byk Mac® device from Byk-Gardner, or under-sampled bidirectional reflectance devices such as the MA98 device from X-Rite, Inc. While these devices demonstrate an improvement over the existing portable equipment available to provide coarseness, sparkle, and additional previously unavailable information, the devices do not provide simple data streams or conclusive texture and opacity information. CCD cameras generating sparkle and graininess values are inaccurate and provide generic values so that pigment identification/characterization and textural information is inaccurate even when used in conjunction with texture scales and spectral data. Under-sampled bidirectional reflectance devices use a complex amount of datastreams and rely on overcomplicated scattering properties of pigments to either “fingerprint” pigments or sample defects.
None of the aforementioned devices provide adequate information for identification of and property analysis of effect pigmentations, such as colored aluminums because, in part, the devices provide inadequate results due to the underlying assumption that coarseness is not an attributable characteristic and only sparkle is an appropriate measure. However, different aluminums (colored or otherwise) clearly demonstrate coarseness qualities in collimated light and thus there may be confusion with regard to visually different aluminum pigments that appear identical to the devices, and the suggested usage of those devices. Furthermore, the devices typically require traditional, advanced, or complex proprietary colorimetric functions that use weighting functions to produce moderate results.
Further strategies have been developed using painted or virtual samples that represent various textures and that are compared to unknown samples. These techniques require substantial user intervention and are subjective in nature and thus may yield inconsistent results depending on the skill of the user.
Thus, a need exists for a simplified approach that uses limited multiangle, multiplanar spectral and/or visual data with or without a color camera that can produce improved and simplified results for pigment characterization and sample properties so that application (opacity) issues and texture issues can be quickly and clearly identified to allow for faster and better color matching.